Gemma 4 26B A4B vs Llama 3.3 70B Instruct
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Gemma 4 26B A4B and Llama 3.3 70B Instruct.
Gemma 4 26B A4B
Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...
Llama 3.3 70B Instruct
Meta's state-of-the-art open weights model, providing enterprise-grade reasoning and logic. Exceptionally powerful for self-hosted customer support, text generation, and tooling workflows.
Technical Specifications
| Specification | Gemma 4 26B A4B | Llama 3.3 70B Instruct |
|---|---|---|
| Provider | Meta | |
| Context Window | 262,144 tokens | 131,072 tokens |
| Agent Suitability | N/A | 83/100 |
| Time to First Token (TTFT) | N/A | 280 ms |
| Deployment Model | managed api | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2026-04-03 | 2024-12-06 |
API Pricing Comparison
Input Price per Million Tokens
Gemma 4 26B A4B
$0.06
Llama 3.3 70B Instruct
$0.10
Output Price per Million Tokens
Gemma 4 26B A4B
$0.33
Llama 3.3 70B Instruct
$0.32
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Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
Gemma 4 26B A4B Quirks & Gotchas
No developer gotchas reported.
Llama 3.3 70B Instruct Quirks & Gotchas
- ▸Stable, well-documented self-hosted option with strong community support
- ▸Outperformed by Llama 4 Maverick for agentic tool-calling workflows